دورية أكاديمية

Model-informed classification of broadband acoustic backscatter from zooplankton in an in situ mesocosm

التفاصيل البيبلوغرافية
العنوان: Model-informed classification of broadband acoustic backscatter from zooplankton in an in situ mesocosm
المؤلفون: Dunn, Muriel, McGowan-Yallop, Chelsey, Pedersen, Geir, Falk-Petersen, Stig, Daase, Malin, Last, Kim, Langbehn, Tom J, Fielding, Sophie, Brierley, Andrew S, Cottier, Finlo, Basedow, Sünnje L, Camus, Lionel, Geoffroy, Maxime, Wieczorek, Alina
بيانات النشر: Oxford University Press
سنة النشر: 2023
المجموعة: Natural Environment Research Council: NERC Open Research Archive
الوصف: Classification of zooplankton to species with broadband echosounder data could increase the taxonomic resolution of acoustic surveys and reduce the dependence on net and trawl samples for ‘ground truthing’. Supervised classification with broadband echosounder data is limited by the acquisition of validated data required to train machine learning algorithms (‘classifiers’). We tested the hypothesis that acoustic scattering models could be used to train classifiers for remote classification of zooplankton. Three classifiers were trained with data from scattering models of four Arctic zooplankton groups (copepods, euphausiids, chaetognaths, and hydrozoans). We evaluated classifier predictions against observations of a mixed zooplankton community in a submerged purpose-built mesocosm (12 m3) insonified with broadband transmissions (185–255 kHz). The mesocosm was deployed from a wharf in Ny-Ålesund, Svalbard, during the Arctic polar night in January 2022. We detected 7722 tracked single targets, which were used to evaluate the classifier predictions of measured zooplankton targets. The classifiers could differentiate copepods from the other groups reasonably well, but they could not differentiate euphausiids, chaetognaths, and hydrozoans reliably due to the similarities in their modelled target spectra. We recommend that model-informed classification of zooplankton from broadband acoustic signals be used with caution until a better understanding of in situ target spectra variability is gained.
نوع الوثيقة: article in journal/newspaper
وصف الملف: text
اللغة: English
العلاقة: https://nora.nerc.ac.uk/id/eprint/536454/1/fsad192.pdfTest; Dunn, Muriel; McGowan-Yallop, Chelsey; Pedersen, Geir; Falk-Petersen, Stig; Daase, Malin; Last, Kim; Langbehn, Tom J; Fielding, Sophie orcid:0000-0002-3152-4742; Brierley, Andrew S; Cottier, Finlo; Basedow, Sünnje L; Camus, Lionel; Geoffroy, Maxime; Wieczorek, Alina. 2023 Model-informed classification of broadband acoustic backscatter from zooplankton in an in situ mesocosm. ICES Journal of Marine Science, fsad192. https://doi.org/10.1093/icesjms/fsad192Test
DOI: 10.1093/icesjms/fsad192/7460294
الإتاحة: https://doi.org/10.1093/icesjms/fsad192Test
http://nora.nerc.ac.uk/id/eprint/536454Test/
https://nora.nerc.ac.uk/id/eprint/536454/1/fsad192.pdfTest
حقوق: cc_by_4
رقم الانضمام: edsbas.9814BD1F
قاعدة البيانات: BASE